Telcos Aiming To Boost Customer Care Through Big Data
December 14, 2015
Earlier this year, Guavus sponsored a big data survey report by Heavy Reading. The results mirror what we are finding with our own customers. Using big data analytics applications for Customer care solutions will be the top priority for telecommunications companies in the coming years.
Research revealed that 87 per cent of network providers have either already implemented a big data strategy or are in the process of doing so. The primary drivers for the adoption of such services include maximising revenue, named by 66 per cent of respondents, boosting customer experience and loyalty (61 per cent), and cutting operational expenditures (also 61 per cent).
However, in the next two years, it will be improving customer care that will be the focus of these activities. The study found that 57 per cent of respondents named this as their top issue they are looking to address over the period, ahead of revenue assurance (48 per cent), improving targeted offerings (47 per cent) and better service assurance (44 per cent).
It is no surprise to see that proactive customer care will be the top area of investment for 2016 and beyond, as in today’s competitive environment providing a seamless customer experience holds the key to safeguarding operator revenue streams and will be the key to differentiation moving forward.
Being able to gain a complete, end-to-end picture of subscribers’ experiences enables telcos to intervene quickly as soon as potential issues are detected. This means they can remedy any service degradations, prevent churn and raise customer satisfaction for increased loyalty – ultimately leading to improved revenue.
As companies become more familiar with big data and their strategies mature, the focus is shifting away from simply collecting and analyzing very large data sets towards being able to derive actionable intelligence from their information.
Ou operator customers have realized that the ability to fuse data streams and bridge the gap between business and operational data is essential to achieving this goal. However, it’s also vital to strip out only the most valuable nuggets of data for analysis, as trying to store everything will increase costs, delay time to insight and devalue the quality of the analytics provided.
An inability to integrate data from disparate systems is currently one of the biggest barriers to success for many telcos, with 28 per cent of respondents listing this as a problem. This was followed by poor data quality and management (25 per cent) and finding personnel with the right skills to handle such projects.
The study also found that a large number of telcos remain dubious over the value of data lakes, despite the fact these solutions have been hyped as one of the keys to big data success. Only 22 per cent of respondents said data lakes are a critical part of how they bring disparate data together, while some 68 percent of network operators stated they remain unsure about these tools, or are waiting to see whether they will emerge as more than just hype. We see data lakes as important way to more cost effectively storing data, but they are not enough in their own right to solve business problems and provide the data science to address specific issues. Guavus analytics applications integrate with our customers’ data lakes.